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Record W2976145333 · doi:10.1101/782201

Standing genetic variation and chromosomal rearrangements facilitate local adaptation in a marine fish

2019· preprint· en· W2976145333 on OpenAlexafffund
Hugo Cayuela, Quentin Rougemont, Martin Laporte, Claire Mérot, Éric Normandeau, Yann Dorant, Ole K. Tørresen, Siv Nam Khang Hoff, Sissel Jentoft, Pascal Sirois, Martín Castonguay, Teunis Jansen, Kim Præbel, Marie Clément, Louis Bernatchez

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2019
Typepreprint
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic diversity and population structure
Canadian institutionsMemorial University of NewfoundlandFisheries and Oceans CanadaUniversité du Québec à Chicoutimi
FundersFisheries and Oceans CanadaNatural Sciences and Engineering Research Council of CanadaPinngortitaleriffikWorld Wildlife Fund
KeywordsBiologyLocal adaptationCapelinGene flowEvolutionary biologyReproductive isolationAdaptation (eye)Genetic divergenceBiological dispersalGenetic variationMallotusPopulationDemographic historyGeneticsEcologyGeneGenetic diversity

Abstract

fetched live from OpenAlex

Abstract Population genetic theory states that adaptation most frequently occurs from standing genetic variation, which results from the interplay between different evolutionary processes including mutation, chromosomal rearrangements, drift, gene flow and selection. To date, empirical work focusing on the contribution of standing genetic variation to local adaptation in the presence of high gene flow has been limited to a restricted number of study systems. Marine organisms are excellent biological models to address this issue since many species have to cope with variable environmental conditions acting as selective agents despite high dispersal abilities. In this study, we examined how, demographic history, standing genetic variation linked to chromosomal rearrangements and shared polymorphism among glacial lineages contribute to local adaptation to environmental conditions in the marine fish, the capelin ( Mallotus villosus ). We used a comprehensive dataset of genome-wide single nucleotide polymorphisms (25,904 filtered SNPs) genotyped in 1,359 individuals collected from 31 spawning sites in the northwest Atlantic (North America and Greenland waters). First, we reconstructed the history of divergence among three glacial lineages and showed that they diverged from 3.8 to 1.8 MyA. Depending on the pair of lineages considered, historical demographic modelling provided evidence for divergence with gene flow and secondary contacts, shaped by barriers to gene flow and linked selection. We next identified candidate loci associated with reproductive isolation of these lineages. Given the absence of physical or geographic barriers, we thus propose that these lineages may represent three cryptic species of capelin. Within each of these, our analyses provided evidence for large N e and high gene flow at both historical and contemporary time scales among spawning sites. Furthermore, we detected a polymorphic chromosomal rearrangement leading to the coexistence of three haplogroups within the Northwest Atlantic lineage, but absent in the other two clades. Genotype-environment associations revealed molecular signatures of local adaptation to environmental conditions prevailing at spawning sites. Altogether, our study shows that standing genetic variation associated with both chromosomal rearrangements and ancestral polymorphism contribute to local adaptation in the presence of high gene flow.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.016
GPT teacher head0.203
Teacher spread0.188 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations10
Published2019
Admission routes2
Has abstractyes

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